BioSimWare: A Software for the Modeling, Simulation and Analysis of Biological Systems

BioSim Ware is a novel software that provides a user-friendly framework for the modeling and stochastic simulation of complex biological systems, ranging from cellular processes to population phenomena. BioSim Ware implements several stochastic algorithms to simulate the dynamics of single or multivolume models, as well as automatic tools to analyze the effect of variation of the system parameters. BioSim Ware supports SBML format, and can automatically convert stochastic models into the corresponding deterministic formulation. The main features of BioSim Ware are presented in this paper, together with some applications which highlight the most relevant aspects of the computational tools that it provides.

[1]  J. Tyson Some further studies of nonlinear oscillations in chemical systems , 1973 .

[2]  Saltelli Andrea,et al.  Global Sensitivity Analysis: The Primer , 2008 .

[3]  J Timmer,et al.  Parameter estimation in stochastic biochemical reactions. , 2006, Systems biology.

[4]  Carmen G. Moles,et al.  Parameter estimation in biochemical pathways: a comparison of global optimization methods. , 2003, Genome research.

[5]  Luis Serrano,et al.  Space as the final frontier in stochastic simulations of biological systems , 2005, FEBS letters.

[6]  Giancarlo Mauri,et al.  A study on the combined interplay between stochastic fluctuations and the number of flagella in bacterial chemotaxis , 2009, COMPMOD.

[7]  Vipul Periwal,et al.  System Modeling in Cellular Biology: From Concepts to Nuts and Bolts , 2006 .

[8]  Daniel T Gillespie,et al.  Stochastic simulation of chemical kinetics. , 2007, Annual review of physical chemistry.

[9]  M. Feinberg,et al.  Understanding bistability in complex enzyme-driven reaction networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[10]  P. Swain,et al.  Stochastic Gene Expression in a Single Cell , 2002, Science.

[11]  Giancarlo Mauri,et al.  A Multi-volume Approach to Stochastic Modeling with Membrane Systems , 2009, Algorithmic Bioprocesses.

[12]  G. Wadhams,et al.  Making sense of it all: bacterial chemotaxis , 2004, Nature Reviews Molecular Cell Biology.

[13]  Pawan Dhar,et al.  Modeling and simulation of biological systems with stochasticity , 2004, Silico Biol..

[14]  Axel Kowald,et al.  Systems Biology - a Textbook , 2016 .

[15]  Hong Qian,et al.  Stochastic dynamics and non-equilibrium thermodynamics of a bistable chemical system: the Schlögl model revisited , 2009, Journal of The Royal Society Interface.

[16]  Hiroaki Kitano,et al.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..

[17]  A. Saltelli,et al.  Sensitivity analysis for chemical models. , 2005, Chemical reviews.

[18]  Adam P. Arkin,et al.  Efficient stochastic sensitivity analysis of discrete event systems , 2007, J. Comput. Phys..

[19]  Vipul Periwal,et al.  The Role of Modeling in Systems Biology , 2006 .

[20]  A. Arkin,et al.  Stochastic mechanisms in gene expression. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[21]  Giancarlo Mauri,et al.  A Novel Variant of P Systems for the Modelling and Simulation of Biochemical Systems , 2009, Workshop on Membrane Computing.

[22]  Daniel T. Gillespie,et al.  Simulation Methods in Systems Biology , 2008, SFM.

[23]  Giancarlo Mauri,et al.  Tau Leaping Stochastic Simulation Method in P Systems , 2006, Workshop on Membrane Computing.

[24]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[25]  D. Bray,et al.  Simulated Diffusion of Phosphorylated CheY through the Cytoplasm of Escherichia coli , 2005, Journal of bacteriology.

[26]  Darren J. Wilkinson Stochastic Modelling for Systems Biology , 2006 .

[27]  Marco Bernardo,et al.  Formal Methods for Computational Systems Biology, 8th International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFM 2008, Bertinoro, Italy, June 2-7, 2008, Advanced Lectures , 2008, SFM.

[28]  G. Moseley,et al.  Targeted delivery to the nucleus. , 2007, Advanced drug delivery reviews.

[29]  Aviv Regev,et al.  Representation and Simulation of Biochemical Processes Using the pi-Calculus Process Algebra , 2000, Pacific Symposium on Biocomputing.

[30]  Arto Salomaa,et al.  Algorithmic Bioprocesses , 2009, Natural Computing Series.

[31]  Gheorghe Paun,et al.  Computing with Membranes , 2000, J. Comput. Syst. Sci..

[32]  Giancarlo Mauri,et al.  Stochastic Simulations on a Grid Framework for Parameter Sweep Applications in Biological Models , 2009, 2009 International Workshop on High Performance Computational Systems Biology.

[33]  Yang Cao,et al.  Sensitivity analysis of discrete stochastic systems. , 2005, Biophysical journal.

[34]  J. R. Pomerening,et al.  Uncovering mechanisms of bistability in biological systems. , 2008, Current opinion in biotechnology.

[35]  D. Gillespie Approximate accelerated stochastic simulation of chemically reacting systems , 2001 .

[36]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[37]  J. Elf,et al.  Spontaneous separation of bi-stable biochemical systems into spatial domains of opposite phases. , 2004, Systems biology.

[38]  Thomas Wilhelm,et al.  The smallest chemical reaction system with bistability , 2009, BMC Systems Biology.

[39]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[40]  Linda R Petzold,et al.  The slow-scale stochastic simulation algorithm. , 2005, The Journal of chemical physics.

[41]  Paolo Cazzaniga,et al.  Computing with energy and chemical reactions , 2009, Natural Computing.

[42]  Paolo Milazzo,et al.  The Calculus of Looping Sequences , 2008, SFM.

[43]  Javier Macía,et al.  Monomeric Bistability and the Role of Autoloops in Gene Regulation , 2009, PloS one.

[44]  Muruhan Rathinam,et al.  Stiffness in stochastic chemically reacting systems: The implicit tau-leaping method , 2003 .

[45]  Giancarlo Mauri,et al.  An Analysis on the Influence of Network Topologies on Local and Global Dynamics of Metapopulation Systems , 2010, AMCA-POP.

[46]  Giancarlo Mauri,et al.  Seasonal variance in P system models for metapopulations , 2007 .

[47]  Linda R Petzold,et al.  Adaptive explicit-implicit tau-leaping method with automatic tau selection. , 2007, The Journal of chemical physics.

[48]  Giancarlo Mauri,et al.  A Comparison of Genetic Algorithms and Particle Swarm Optimization for Parameter Estimation in Stochastic Biochemical Systems , 2009, EvoBIO.

[49]  Giancarlo Mauri,et al.  Dynamical probabilistic P systems , 2006, Int. J. Found. Comput. Sci..

[50]  Alfonso Rodríguez-Patón,et al.  A New Class of Symbolic Abstract Neural Nets: Tissue P Systems , 2002, COCOON.

[51]  Cazzaniga Stochastic algorithms for biochemical processes , 2010 .

[52]  D. Gillespie Exact Stochastic Simulation of Coupled Chemical Reactions , 1977 .

[53]  Mads Kærn,et al.  Noise in eukaryotic gene expression , 2003, Nature.

[54]  E. Martegani,et al.  Modeling and stochastic simulation of the Ras/cAMP/PKA pathway in the yeast Saccharomyces cerevisiae evidences a key regulatory function for intracellular guanine nucleotides pools. , 2008, Journal of biotechnology.

[55]  Gheorghe Paun,et al.  The Oxford Handbook of Membrane Computing , 2010 .

[56]  Linda R Petzold,et al.  Efficient step size selection for the tau-leaping simulation method. , 2006, The Journal of chemical physics.

[57]  D. Gillespie A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions , 1976 .

[58]  Giancarlo Mauri,et al.  Modelling metapopulations with stochastic membrane systems , 2008, Biosyst..

[59]  Shuangzhe Liu,et al.  Global Sensitivity Analysis: The Primer by Andrea Saltelli, Marco Ratto, Terry Andres, Francesca Campolongo, Jessica Cariboni, Debora Gatelli, Michaela Saisana, Stefano Tarantola , 2008 .

[60]  Tatiana T Marquez-Lago,et al.  Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics. , 2007, The Journal of chemical physics.

[61]  Kevin Burrage,et al.  Stochastic approaches for modelling in vivo reactions , 2004, Comput. Biol. Chem..

[62]  Claudine Chaouiya,et al.  Petri net modelling of biological networks , 2007, Briefings Bioinform..

[63]  Giancarlo Mauri,et al.  Modeling Diffusion in a Signal Transduction Pathway: the Use of Virtual Volumes in P Systems , 2011, Int. J. Found. Comput. Sci..